Georg Groh

Georg Groh is an Adjunct Professor at the Technical University of Munich (TUM), affiliated with the TUM School of Computation, Information and Technology. His research focuses on modeling social context, social interaction mediated by IT systems, and ML-based natural language processing. He holds a doctorate (2005) and habilitation (2012) from TUM, with prior studies in physics and computer science. Key research areas include social signal processing, network analysis, and bias detection in AI systems. Notable awards include the 2019 Supervisory Award and 2016 Honorary Teaching Certificate. His work bridges computational methods with societal impacts, particularly in health informatics and ethical AI. Recent projects explore LLM hallucination detection, bias profiling, and cross-lingual text classification.

Education:

• PhD in Computer Science (2005), TUM
• Habilitation in Computer Science (2012), TUM
• Studies in Physics (University of Kaiserslautern) and Computer Science (Universities of Hamburg, Kaiserslautern, TUM)

Research Interests: Groh’s work spans social computing, NLP, and ethical AI. Current projects address bias in language models, hate speech detection, and data-driven health interventions. His methodologies emphasize contextual analysis of social interactions, leveraging ML and graph-based techniques.

Awards:

• 2nd place Supervisory Award (2019)
• Best Paper Awards (2016, 2008)

Advising & Grants: Advised on projects like Nutrilize (nutrition recommender system) and contributed to EU-funded initiatives on mHealth systems. Active in designing AI systems for dietary logging and stress management.